Causal mediation analysis in nested case-control studies using conditional logistic regression
Not provided.
Mathematical & Computational Biology↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition
Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.
Hanson, Joshua↗
Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments
The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.
36 MATERIALS SCIENCE↗
Plasma-Assisted Epitaxy of Piezoelectric Sc x Al 1-x N Films on Sapphire for Use in Harsh-Environment Microwave Acoustic Sensors
The Sc x Al 1-x N wurtzite structure has been shown theoretically and experimentally to exhibit significantly higher piezoelectric coupling compared to pure AlN. In this work, a plasma-assisted epitaxial growth method has been used to synthesize epitaxial (0002) Sc x Al 1-x N films on c-sapphire substrates from x = 0.07 to 0.30 by co-evaporating high-purity Sc and Al sources in the presence of a nitrogen plasma generated by an RF plasma source. Epitaxial Sc x Al 1-x N films with highly oriented (0002) grains and in-plane registry were produced on c-sapphire substrates that were pre-exposed to the nitrogen plasma to form an oxynitride seed layer. Growth of Sc x Al 1-x N films was carried out at 930°C under both metal-rich and N-rich conditions using precisely controlled Sc, Al, and N-plasma fluxes. Metal-rich depositions yielded non-(0002)-oriented Sc x Al 1-x N grains and intermetallic ScAl grains. Nitrogen-rich growth with a Sc/Al flux ratio of 1/3 produced the best (0002) epitaxy as determined by x-ray diffraction analysis. Surface acoustic wave resonator (SAWR) devices were fabricated from 500-nm-thick Sc x Al 1-x N and AlN films to extract their electromechanical coupling coefficients, k 2 . As the Sc concentration in the films increases, the degree of (0002) epitaxy is reduced, yet the value of k 2 increases becasue there is more Sc in the wurzite lattice despite the decreased level of (0002) grain alignment. As a result, the use of a 10-nm-thick Si x N y capping layer on top of the Sc x Al 1-x N films aids in preventing etching during SAWR device photolithography and also helps hinder film oxidation up to 800°C.
36 MATERIALS SCIENCE↗
Examining material constitutive response under dynamic compression and large plastic strains using in situ imaging of hole closure
Abstract not provided
Lind, Jonathan↗
Tree growth, transpiration, and water-use efficiency between shoreline and upland red maple (Acer rubrum) trees in a coastal forest
Coastal shoreline forests are vulnerable to seawater exposure, the impacts of which will increase due to sea-level rise, but the longterm adaption strategies and vulnerability of coastal forests are not well understood. We used whole-tree transpiration, leaf water potential, tree-ring width, and tree-ring d13C (a proxy for intrinsic water use efficiency, iWUE) to examine the long-term adaption strategies of red maple (Acer rubrum) trees at the coastal interface (i.e., shoreline) and nearby upland in Maryland, USA. Red maple trees that grew along the shoreline and were exposed to slightly saline water (up to two PSU) had higher transpiration rates than those growing in the nearby upland forest during a wet year, but these differences disappeared during a normal precipitation year. Shoreline trees grew more slowly than upland trees over the last four decades, but these growth differences have disappeared in the last six years. Shoreline and upland trees had similar variation in iWUE, indicating that higher transpiration rates of the seawater exposed trees did not translate into differences in water use efficiency. There were no differences in predawn and midday water potential between upland and shoreline trees, suggesting no water stress occurs in shoreline trees. These findings indicate that urrent soil salinity is below the threshold to constrain coastal red maple physiological activities.
Wang, Wenzhi↗
Predicting PEMFC performance from a volumetric image of catalyst layer structure using pore network modeling
Not Available
Sadeghi, Mohammad Amin↗
Optimizing Phase Change Composite Thermal Energy Storage Using the Thermal Ragone Framework
The thermal Ragone framework can be applied to the design of thermal energy storage heat exchangers to identifying relationships between their power requirements and energy capabilities. This presentation focuses on the design of planar thermal energy storage heat exchangers with phase change materials and thermal conductivity additives. Finite-difference models were used to optimize thermal storage heat exchanger designs focusing on key design parameters of conductivity additive volume fraction, spacing between tubes, and the phase transition temperatures. Design trends were developed for optimal designs based on varying thermal power requirements. To aid in future device design, models of reduced complexity were developed with the ability to predict optimal designs with computational speeds up to 5,000 times faster than finite-difference models.
ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗
Determination of low-level biogenic gasoline, jet fuel, and diesel in blends using the direct liquid scintillation counting method for 14C content
Not Available
Doll, Charles G. (ORCID:000000015235807X)↗
Towards a circular economy for PET bottle resin using a system dynamics inspired material flow model
Not Available
Ghosh, Tapajyoti (ORCID:0000000205220235)↗
Cold Spray Deposition of 304L Stainless Steel to Mitigate Chloride-Induced Stress Corrosion Cracking in Canisters for Used Nuclear Fuel Storage
A feasibility study of the cold spray deposition process of 304L stainless steel on 304L stainless steel substrates as a mitigation method for chloride-induced stress corrosion cracking (CISCC) has been investigated under various substrate conditions. The study is aimed at the application of this technology to mitigate CISCC that may potentially occur in or nearthe fusion welded regions of stainless steel canisters in Dry Cask Storage System (DCSS) for used nuclear fuels. Spherical gas-atomized 304L stainless steel powder, in the size range of 25 µm to 44 µm, was used as a feedstock powder for the cold spray process. The powder was deposited on four types of 304L substrates with various surface conditions: as-polished, oxidized, cold-rolled, plates with prototypical CISCC. The effects of cold spray parameters on quality of cold spray coatings were investigated. Thickness, porosity, and phases in the as-deposited materials were evaluated using scanning electron microscopy (SEM) and X-ray diffraction (XRD), and correlated with microhardness and adhesion strength measured via micro-indentation and ASTM C633 pulling test, respectively. XRD analysis of the coatings was also conducted to examine the effects of cold spray condition on residual stress state in the coating. Detailed cross-sectional examination of coating/substrate interfaces was performed with transmission electron microscopy (TEM) equipped with energy dispersive spectroscopy (EDS). Dense and continuous coatings with good adhesion strength and hardness were produced for the various substrate conditions by adjusting cold spray parameters. The results demonstrate that cold spray stainless steel coating is a viable option to provide a physical barrier against CISCC in fusion weld regions of stainless steel in corrosive chloride salt-bearing environments.
Dry Cask Storage Systems, cold spray, 304L stainle↗
Micrometer-sized Magnetite Synthesis using Fe(OH)2(s) as a Precursor for Technetium Sequestration from Liquid Nuclear Waste Streams
Systematic batch experiments under variable adjusted physicochemical conditions were conducted to explore optimization of micrometer-sized magnetite synthesis for Tc sequestration from radionuclide waste streams using Fe(OH)2(s) as the precursor. Extensive solid characterization using x-ray diffraction and spectroscopic methods was performed to assess changes in particle morphology and size distribution, as well as Tc speciation and incorporation, in the produced mineral phases. The results show that the solution pH, temperature, and oxidation kinetics play key roles in the final mineral products. Micrometer-sized magnetite crystals (0.62-0.96 µm on average) with well-defined dodecahedral or octahedral structures were synthesized under near neutral (~pH 8) or alkaline (~pH13) conditions at 75 °C, respectively; whereas goethite dominated the end products at room temperature. An increase in pH at 75 °C improved Tc removal from 27% (near neutral pH) to 42% (alkaline pH), but the removal process remained inhibited by redox competitive Cr(VI) present in the waste streams. By adding additional Fe(II) to the system, Tc sequestration was dramatically improved to up to 87% without observable changes in the solid product. The sequestrated Tc existed as TcO2·2H2O and/or Tc(IV) incorporated into magnetite, where extended X-ray absorption fine structure (EXAFS) spectroscopy showed that more Tc was incorporated into magnetite at elevated temperatures and pH conditions, with complete Tc(IV) incorporation into magnetite occurring under 75 °C-pH 13 conditions. Our results indicate that optimal micrometer-sized magnetite can be produced for Tc sequestration by reacting Fe(OH)2(s) with a waste stream simulant under elevated pH (~13) and temperature (75 °C) conditions. The incorporation of reduced Tc(IV) into stable micrometer-sized magnetite provides a viable supplemental immobilizing technology that may be used to improve nuclear waste treatment and disposal needs.
Wang, Guohui↗
Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm
The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.
79 ASTRONOMY AND ASTROPHYSICS↗
Cross-database comparisons on the greenhouse gas emissions, water consumption, and fossil-fuel use of plastic resin production and their post-use phase impacts
Resin production and post-use pathways have cross-database discrepancies due to different temporal/geographic representation, technologies, and assumptions. These differences can distort comparisons across alternatives and confound efforts to establish standards based on the plastics’ life-cycle impacts. Thus, this study quantifies the degree and identifies the sources of cross-database discrepancies across four LCA databases (GREET, USLCI, Ecoinvent, and GaBi) for five resin production pathways and three post-use phases. For resin production pathways, all resins showed significant cross-database discrepancy in their global warming impacts: the degree of discrepancy was significant to recommend a consistent choice of database to users any LCA comparisons across different products. For post-use phases, landfill datasets had relatively lower degree of cross-database discrepancy than incineration and mechanical recycling. Different metadata characteristics were the sources of some cross-database discrepancies while other parts could be explained by the original differences in the life-cycle inventory sourced from different producers and plants.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Intrinsic Li Distribution in Layered Transition-Metal Oxides Using Low-Dose Scanning Transmission Electron Microscopy and Spectroscopy
Understanding Li distribution in layered lithium transition-metal oxide (LiTMO) cathodes in Li-ion batteries has been a major challenge at the atomic scale and nanoscale. Li is extremely difficult to study by transmission electron microscopy (TEM) because the high-energy electrons impart significant energy and cause massive migration. Here, we directly map the intrinsic spatial distribution and bonding of Li in LiNiO 2 -layered cathode materials using low-dose and low-loss electron energy loss spectroscopy (EELS). EELS spectra of the Li–K edge are measured simultaneously with O–K and Ni–L, M 3,2 edges from layered, cation-mixed, and rock-salt phases and directly matched with atomic-resolution scanning TEM images to correlate the changes in peak intensities and positions to the stoichiometry changes with continual loss of Li and O. Changes in the Li content in the LiNiO 2 particles as a function of electron beam dose are studied by sequential Li spectroscopic mapping. We show that the “intrinsic” Li distribution can be observed using a total dose of less than ~1.5 × 10 8 e – nm –2 at an accelerating voltage of 80 kV. The method of nanoscale mapping of Li distribution introduced in this study is applicable to high-Ni LiTMO cathode materials (>89% of Ni) as well as LiNiO 2 . Further study on the extra peaks of the Li–K edge reveals that the peak at ~59 eV is from the Li ions intercalated in between NiO 2 layers barely interacting with each other with less Li K shell electrons pulled to the L shell electrons in NiO 2 . Furthermore, the results shown here provide improved low-loss TEM characterization approaches that can be used to understand the intrinsic fundamental behaviors in Li-ion batteries.
25 ENERGY STORAGE↗
Balancing Water Sustainability and Productivity Objectives in Microalgae Cultivation: Siting Open Ponds by Considering Seasonal Water-Stress Impact Using AWARE-US
Microalgae have great potential as an energy crop. Scaling-up algal biofuel production in the United States (US) should be done with careful attention to water stress. This study evaluates the regional and seasonal water-stress impact of potential algae-pond deployments in the US. Three site-selection strategies focusing on biomass yield, water-use efficiency (WUE), and water-stress impact, respectively, are applied and compared to meet a US algae biomass production target of 30 million metric tons/yr ash-free dry weight, which converts to 20.8 billion L renewable diesel, via hydrothermal liquefaction. Ranking algae ponds based on biomass yield leads to freshwater consumption of 2.66 km3/yr, resulting in the highest water-stress impact (39.1 US equivalent km3). Under the WUE scenario, water consumption is reduced by 81%, but biomass yield is reduced by 12%. In contrast, adding a water-stress constraint to the biomass-yield ranking reduces water consumption by 50% and water-stress impact by 97%, with a small yield reduction (1.7%). Results show that pond location has a significant effect on water stress and that water stress is not proportional to water consumption or yield. Furthermore, capturing seasonal water patterns is critical for planning because sites in water-abundant regions can have short-term but significant water-stress impacts.
algae, Biofuel, water scarcity footprint, hydrothe↗
Facile Oxidation of Ce(III) to Ce(IV) Using Cu(I) Salts
The synthesis, luminescence, and electrochemical properties of the Ce(III) compound, [(C 5 Me 5 )2(2,6- i Pr 2 C 6 H 3 O)Ce(THF)], 1, were investigated. Based on the electrochemical data, treatment of 1 with CuX (X = Cl, Br, I) results in the formation of the corresponding Ce(IV) complexes, [(C 5 Me 5 ) 2 (2,6- i Pr 2 C 6 H 3 O)Ce(X)]. Each complex has been characterized using NMR, IR, and UV−vis spectroscopy as well as structurally determined using X-ray crystallography. Additionally, the treatment of [(C 5 Me 5 ) 2 (2,6- i Pr 2 C 6 H 3 O)Ce(Br)] with AgF results in the formation of the putative [(C 5 Me 5 ) 2 (2,6- i Pr 2 C 6 H 3 O)Ce(F)]. Furthermore, the electronic structure of these Ce(IV)−X complexes was investigated by bond analyses and the Ce(IV)−F moiety using quantum chemistry NMR calculations.
Aromatic compounds↗